影像与基因特征分析方法在阿尔茨海默病中的研究进展

doi:10.3969/j.issn.0258-8021.2022.04.011

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Abstract Alzheimer′s disease (AD) is one of the most common neurodegenerative diseases, and its phenotype has shown susceptible to genetic factors. In recent years, with the wide application of multimodal brain imaging and high-throughput genomics in medical imaging, it has become a new hotspot to explore the association analysis between images and genes by means of data mining and mathematical modeling. Till now, the combined analysis of images and genetic characteristics has been used to study AD and has made significant progress in the early diagnosis, classification, and prognostic analysis. This article first summarized the imaging and genetic features, then explained the application of statistics and machine learning (ML) methods in the joint analysis of image gene features, and finally summarized and proposed its development perspectives.

Key words： imaging and genetic features Alzheimer′s disease machine learning statistical methods deep learning

Received: 09 October 2020

PACS:

R318

Corresponding Authors: ^*E-mail: yao6636329@hotmail.com

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	Articles by authors
	Han Liting
	Yao Xufeng
	Jin Yu
	Zhao Congyi
	Huang Gang

Cite this article:

Han Liting,Yao Xufeng,Jin Yu, et al. Research Progress for the Analysis of Images and Genetic Features in Alzheimer′s Disease[J]. Chinese Journal of Biomedical Engineering, 2022, 41(4): 485-492.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2022.04.011 OR http://cjbme.csbme.org/EN/Y2022/V41/I4/485

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